Quick Estimation of Resources of FPGAs and ASICs Using Neural Networks

Monostori A, Frühauf HH, Kókai G (2005)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2005

Edited Volumes: Lernen, Wissensentdeckung und Adaptivitat, LWA 2005

Pages Range: 210-215

Conference Proceedings Title: LWA 2005 - Beiträge zur GI-Workshopwoche Lernen, Wissensentdeckung, Adaptivität

Event location: Saarbrücken, Germany DE

URI: http://www2.informatik.uni-erlangen.de/publication/download/lwa05-Kokai.pdf

Abstract

The redFIR2 project at the Fraunhofer Institute for Integrated Circuits is a tool that provides optimised Finite Impulse Response structures. The generation process of these structures is based on a component library containing seven scalable basismodules. Depending on the chosen Integrated Circuit technology and on the I/O wordlengths the resource utilisation of the modules differ considerably. A fast, a priori estimation of resources during the system-level design is of crucial importance for the generation of resource optimised (adjusted to an Integrated Circuit technology) Intellectual Property cores. The objective of this work is to develop a flexible, adaptive resource estimation methodology.

How to cite

APA:

Monostori, A., Frühauf, H.H., & Kókai, G. (2005). Quick Estimation of Resources of FPGAs and ASICs Using Neural Networks. In Bauer, Mathias ; Kröner, Alexander ; Brandherm, Boris (Eds.), LWA 2005 - Beiträge zur GI-Workshopwoche Lernen, Wissensentdeckung, Adaptivität (pp. 210-215). Saarbrücken, Germany, DE.

MLA:

Monostori, Adam, Hans Holm Frühauf, and Gabriella Kókai. "Quick Estimation of Resources of FPGAs and ASICs Using Neural Networks." Proceedings of the Workshop der GI-Fachgruppe "Maschinelles Lernen, Wissensentdeckung, Data Mining" (FGML), Saarbrücken, Germany Ed. Bauer, Mathias ; Kröner, Alexander ; Brandherm, Boris, 2005. 210-215.

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